The global AIDS epidemic is one of the greatest threats to human health and development. Countries need to ground their AIDS strategies in an understanding of their own epidemics and their national responses. A reliable estimation and prediction on the HIV/AIDS epidemic can help policy makers and program planners ef?ciently allocate the resource, plan and manage the intervention, treatment and care programs, evaluate their effort, and raise funds. The epidemiological model called EPP has been used by the UNAIDS and most countries in the world for estimation and short-term prediction of HIV/AIDS trends from limited surveillance data since 2001. As the epidemic enters its fourth decade, both the epidemic and monitoring data sources have changed signi?cantly. The existing models are no longer capable of capturing the epidemic trend accurately. In this proposal, we plan to develop new statistical models to estimate and project the epidemic that re?ect those changes and utilize new data sources, with the following aims. 1. We will develop a statistical model that makes use of the various sources of available data that have never been used together in a systematic way to jointly model the prevalence and incidence of the HIV epidemic. 2. Key populations and geographic hotspots have become the driver of the epidemic. Policies and interventions require more accurate estimates of the epidemics at the sub-national and sub-population level. Currently, the epidemic models have been applied independently to the sub-national areas within countries and to key populations in concentrated epidemics. However, the availability and quality of the data vary widely, which leads to biased and unreliable estimates for areas and sub-populations with very few data. We propose to overcome this issue by developing a hierarchical model that utilizes data ef?ciently through statistically sharing information across countries, areas and multiple key populations. 3. We will develop an age-speci?c and sex-speci?c model that projects a population strati?ed by infection status and duration of infection. It will be generalized further by adding additional states for HIV positive groups that are receiving antiretroviral treatment. 4. We will produce freely-available, open-source software to implement all of the proposed models and methods.